There are many applications in which radio frequency (RF) or microwave signals are used for tracking objects, such as Global Positioning Systems (GPS), Loran, aircraft navigation, military radar, and video motion capture. All of these use some sort of scheme for detecting the transit times or phases of the RF or microwave signals, followed by a processing or computational subsystem to determine the position and other parameters of the object being tracked.
In some of these applications, such as GPS, Loran, and aircraft navigation systems, the computational intelligence is mounted on the moving object, and the goal is for the operator of the object to determine its own position relative to the surrounding environment. In other applications, the processing capability is attached to the environment, and the goal is for people or systems to track multiple objects as they traverse through the environment.
For example, during navigated medical procedures such as Navigated Surgery (NS) and Image Guided Surgery (IGS) surgeons use electronic surgical instrument tracking to accurately track in real time where the instruments are relative to the patient anatomy during the operation. By combining computers and wireless instruments, navigated surgery systems give surgeons far more accuracy than ever before. During navigated medical procedures, transmitters are mounted on surgical instruments and on bone markers that are attached to a patient's anatomy. Receivers, distributed throughout the operating room, receive signals from the transmitters and use the signals to track instrument position relative to patient anatomy. A graphical interface may be used to display the relative positions of transmitting signals and anatomical markers to enable the surgeon to perform precise medical procedures. Alternatively, a computational model of the patient anatomy and the positions and orientations of the instruments may be used to guide robotic procedures.
Because distances in the medical environment are small and precision requirements are high, methods based on time differences of arrival of signals are not within the state of the art of current electronic technology. For example in an operating room, the positions of a patient's anatomy and of the surgical instruments must be known to a resolution of less than one millimeter (1 mm) in order for computer-assisted or navigated surgery to be viable. Since light travels 1 mm in approximately 3×10−12 seconds, times would have to be measured accurately and repeatably in fractions of picoseconds, something that is beyond the scope of current electronic technology.
An alternative method is to measure the angles between the phases of a transmitted signal as it is received at different receiving antennas. It is possible to measure phase differences with a precision of about 1 percent. Therefore, if the wavelength of a transmitted signal is about 50 mm (i.e., a frequency of about 5.7 GHz), a phase difference of 1 percent translates to a positional precision of about 0.5 mm, which corresponds to a desired precision of navigated medical procedures.
Methods based on time measurements have a relatively simple calculation—d=c*t, where d is the distance between the transmitting and receiving antenna, c is the speed of light in air, and t is the travel time of the transmitted signal. In systems and methods based on phase differences, the computation is more complex. The phase of the received signal must be compared with the phase of a reference signal. The difference in these two phases can be converted into a linear measure, but this is not sufficient to give an absolute distance between the two antennas.
In particular, suppose that φ1 is the phase angle of the received signal (relative to the reference signal) when the transmitting antenna and receiving antenna are distance d1 apart, and suppose that φ2 is the phase angle of the received signal (relative to the reference signal) when those same two antennas are distance d2 apart. Then the difference in the two distances is given by
                              (                                    d              1                        -                          d              2                                )                =                              1                                          2                ⁢                π                ⁢                                                                  ⁢                f                            ⁢                                                                            ⁢                      (                                          ϕ                1                            -                              ϕ                2                            +                              2                ⁢                π                ⁢                                                                  ⁢                                  k                                      1                    ,                    2                                                                        )                                              (                  eq          ⁢                                          ⁢          1                )            where f is the frequency of transmission, the angles φ1 and φ2 are measured in radians, and k1,2 is an integer representing the whole number of wavelengths in the difference (d1−d2). There are many ways of determining k1,2, including some innovative ways that are adapted to particular applications. Likewise, φ1 and φ2 can be known relative to a reference signal, but the absolute phases of φ1 and φ2 are dependent upon the phase delays in the electronics of the transmitter, receiver, and cables. In some applications, particularly medical applications where high precision is required, it is not possible to know these phase delays. As a result, it is also not possible to know a distance such as d1 absolutely, but only relative to some other previously known distance, such as d2.
Therefore, in medical applications (and some other applications), an object must be calibrated by first placing it at a known, fixed location in a frame of reference to determine the phase difference at that location. The object can then be tracked by noting the change in a received phase angle and converting this by Equation 1 to a change in distance from the known, fixed location.
The step of placing the object at the known location is called the object calibration process (or instrument calibration process). For example, in some navigated procedures, each instrument must be inserted into a calibration socket prior to usage, and possibly at times during the procedure. During the object calibration process, signals are transmitted between each antenna on the object and each antenna in that frame of reference. The differences between the phase angles of the received signals and the reference signals are measured and recorded. Collectively, these recorded phase differences are called the phase reference at the origin for that object. All other phase differences (between transmitted signals and reference signals) are then compared with the phase reference at the origin in order to determine how far each antenna has moved since object calibration.
For the purposes of this application, a frame of reference is a three-dimensional geometric coordinate system with respect to which motion is observed and with respect to which measurements are made. It will be appreciated that different applications may have different frames of reference. A typical frame of reference is the operating room in which a navigated medical procedure is performed. However, other applications may use a frame of reference attached to a particular part of the patient anatomy, and still others may associate it with a robotic tool.
Following the calibration, the motion of the object can be tracked by repeatedly measuring the changes in the phase angles between the reference signal and the signals detected by each receiver. In a typical installation, the phase angles are measured periodically at intervals of a small fraction of one second. Provided that the object does not move more than one wavelength during any interval, the change in the phase angle observed by a transmitting antenna and a receiving antenna can be converted into a change in distance between those two antennas. By knowing the changes in the distances between all of the transmitting and receiving antennas and by knowing the positions of the antennas on the moving object, the position of that object relative to its point of calibration can be determined with a desired degree of precision.
In US Patent Application 2006/0066485, Min teaches a system of transmitters and receivers that can detect phase differences of the required precision.
In theory, the change in the position of the object in three-dimensional space can be determined from the changes in the phases of the signal received by three receivers. However, in practical systems, there are a multiplicity of problems and challenges. Among them are:—
a). While three receivers are theoretically sufficient to precisely locate the position of an object in three-dimensional space, and more receivers would be redundant. In practice, different combinations of three receivers determine different positions for an object, due to many possible factors. For example, a receiver may temporarily obstructed from line of sight to the object, the electromagnetic field of the RF waves may be distorted by metal objects or other interference, or the electronics of one receiver may not be as sensitive as another.
b). The relative positions of the antennas are not typically known within a fraction of a wavelength. In practical environments, some antennas may be many wavelengths apart. For example, in an operating room, an array of receiving antennas may be placed 2 meters above the patient (i.e., about 40 wavelengths) and the array itself may be 2 meters in diameter. In some situations, the receiver array may be on a portable cart that is wheeled into position prior to a surgical operation. Therefore, some method of calibrating the antennas in the frame of reference is needed before the positions of any objects can be determined.
c). Radio and microwave signals are subject to “multipath” distortion. That is, a transmitted signal may take multiple paths to the receiver. It is difficult with these methods to differentiate the straight line signal from the interference of signals taking other paths. Methods are needed for filtering out this distortion or for using redundant information to accurately discriminate the positions of objects.
d) In practical applications, one or more receivers may “lose sight” of an object. For example, a person or another object may temporarily get between a transmitter and a receiver, or the object may be dropped, or a transmitted signal may be corrupted or badly distorted. In all of these cases, the continuous tracking of an object from one update cycle to another is lost, and the absolute position of the object becomes ambiguous. Methods are needed to recover the positions of objects lost in this way.
e) A typical application environment will have multiple objects, each with multiple transmitters. In many situations, not only must the position of each object be known but also its orientation. If the geometry of an object is known exactly, it requires at least three antennas on the object to determine its orientation. However, if any signal from any one of those antennas is distorted or blocked, the orientation is lost. Methods are needed to maintain accurate position and orientation information about all of the objects in the field of interest.
f) Some application environments require very frequent updating of position and orientation information. For example, in robotic assisted surgery, all instruments and anatomic markers must refresh position information with frequencies up to 1 kilohertz (1 KHz) or more. Methods are needed that allow such frequent updating.
It would be desirable to determine a system and method that would provide the precise location and orientation of multiple objects with precisions of a small fraction of the wavelengths of the transmitted signals at a frequency that would support robotic assisted surgery.